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by S-CurveLabs

dependency_graph

Read-only

Trace Power Query (M) query lineage to identify upstream and downstream dependencies, plus roots, leaves, orphans, and cyclic references. Output as JSON or Mermaid diagrams.

Instructions

Query-to-query lineage. With query, only its upstream and downstream. format: 'json' or 'mermaid'. Also reports roots (read external data), leaves (final outputs), orphans and cyclic references.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
formatNojson
sourceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds useful behavioral detail beyond that: it reports roots, leaves, orphans, and cyclic references, and supports twp output formats. This gives the agent concrete insight into what the tool computes without contradicting the annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two tight sentences with no filler. It front-loads the core purpose ('Query-to-query lineage') and packs the scoping rule, format options, and output highlights into minimal words. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and no parameter descriptions, the description is incomplete: it never explains the required `source` parameter, the shape of the returned graph, or error/edge behavior. It mentions useful output categories but leaves essential calling details to inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains `query` and `format`, but completely omits `source`, which is a required parameter. For a required argument, leaving its meaning undefined forces the agent to guess, which is a significant gap in a 0%-coverage schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening phrase 'Query-to-query lineage' states the exact resource and operation the tool performs. The sentence 'With query, only its upstream and downstream' clarifies the scoping behavior and distinguishes this from siblings like get_query or list_queries, which return individual or all queries rather than a dependency graph.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to choose dependency_graph over related tools such as find_in_queries, diff_queries, or get_query. The conditional 'With query...' describes parameter behavior, not tool-selection criteria, so an agent gets no help deciding when this tool is the right one.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.